---
title: "Who cites Zilong Wang — 289 papers of our library"
description: "289 papers of the Elamur Research library cite the works of Zilong Wang, found in their bibliographies; the most cited first."
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---
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# Who cites Zilong Wang

291 citations of their works from 289 papers of our library (of the 149,439 whose bibliographies we read) · 48 with a page here, the most cited first · [← Zilong Wang](https://md.research.elamur.ai/free/en/authors/zilong-wang/)

1. [**A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications arXiv:2402.07927**Pranab Sahoo; Ayush Kumar Singh; Sriparna Saha; Vinija Jain; Samrat Mondal;, Aman Chadha*2024 · 375 citations*](https://md.research.elamur.ai/free/en/papers/sahoo-2024-systematic-survey-prompt-engineering-large/)
2. **[A Survey on Large Language Models for Code Generation](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/) [ACM Transactions on Software Engineering and Methodology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-software-engineering-and-methodology/)**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 367 citations*
3. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 301 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
4. **[Large Language Models for Data Annotation and Synthesis: A Survey](https://md.research.elamur.ai/free/en/papers/tan-2024-large-language-models-data-annotation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Tan, Dawei Li, Song Wang, et al.*2024 · 262 citations*
5. [**Debug like a Human: A Large Language Model Debugger via Verifying Runtime Execution Step-by-step arXiv:2402.16906**Li Zhong, Zilong Wang, Jingbo Shang*2024 · 124 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2024-debug-like-human-large-language/)
6. [**A Survey on Efficient Inference for Large Language Models arXiv:2404.14294**Zixuan Zhou, Xuefei Ning, Ke Hong, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-survey-efficient-inference-large-language/)
7. [**Efficient Large Language Models: A Survey arXiv:2312.03863**Zhongwei Wan, Xin Wang, Che Liu, et al.*2023 · 110 citations*](https://md.research.elamur.ai/free/en/papers/wan-2023-efficient-large-language-models-survey/)
8. **[Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems](https://md.research.elamur.ai/free/en/papers/miao-2023-towards-efficient-generative-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, et al.*2023 · 110 citations*
9. [**AFlow: Automating Agentic Workflow Generation arXiv:2410.10762**Jiayi Zhang, Jinyu Xiang, Zhaoyang Yu, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-aflow-automating-agentic-workflow/)
10. [**SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling arXiv:2312.15166**Dahyun Kim, Chanjun Park, Sanghoon Kim, et al.*2023 · 77 citations*](https://md.research.elamur.ai/free/en/papers/kim-2023-solar-10-7b-scaling-large/)
11. [**AI Agents That Matter arXiv:2407.01502**Sayash Kapoor, Benedikt Stroebl, Zachary S. Siegel, et al.*2024 · 55 citations*](https://md.research.elamur.ai/free/en/papers/kapoor-2024-ai-agents-that-matter/)
12. [**RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning arXiv:2410.02089**Jonas Gehring, Kunhao Zheng, Jade Copet, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/gehring-2024-rlef-grounding-code-llms-execution/)
13. **[Fire-Flyer AI-HPC: A Cost-Effective Software-Hardware Co-Design for Deep Learning](https://md.research.elamur.ai/free/en/papers/an-2024-fire-flyer-ai-hpc/) [2012 International Conference for High Performance Computing, Networking, Storage and Analysis](https://md.research.elamur.ai/free/en/venues/2012-international-conference-for-high-performance-computing-networking-storage/)**Wei An, Xiao Bi, Guanting Chen, et al.*2024 · 34 citations*
14. **[Table-Critic: A Multi-Agent Framework for Collaborative Criticism and Refinement in Table Reasoning](https://md.research.elamur.ai/free/en/papers/yu-2025-table-critic-multi-agent-framework/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peiying Yu, Guoxin Chen, Jingjing Wang*2025 · 25 citations*
15. **[AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://md.research.elamur.ai/free/en/papers/chen-2025-ai4research-survey-artificial-intelligence/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Mingda Yang, Libo Qin, et al.*2025 · 21 citations*
16. **[Demons in the Detail: On Implementing Load Balancing Loss for Training Specialized Mixture-of-Expert Models](https://md.research.elamur.ai/free/en/papers/qiu-2025-demons-detail-implementing-load-balancing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zihan Qiu, Zeyu Huang, Bo Zheng, et al.*2025 · 21 citations*
17. **[Beyond Chain-of-Thought: A Survey of Chain-of-X Paradigms for LLMs](https://md.research.elamur.ai/free/en/papers/xia-2025-beyond-chain-thought-survey-chain/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yu Xia, Rui Wang, Xu Liu, et al.*2025 · 19 citations*
18. **[A Survey of Post-Training Scaling in Large Language Models](https://md.research.elamur.ai/free/en/papers/lai-2025-survey-post-training-scaling-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanyu Lai, Xiao Liu, Junjie Gao, et al.*2025 · 18 citations*
19. **[RethinkMCTS: Refining Erroneous Thoughts in Monte Carlo Tree Search for Code Generation](https://md.research.elamur.ai/free/en/papers/li-2025-rethinkmcts-refining-erroneous-thoughts-monte/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Qingyao Li, Wei Xia, Xinyi Dai, et al.*2025 · 16 citations*
20. [**From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging arXiv:2410.01215**Yuling Shi, Songsong Wang, Chengcheng Wan, et al.*2024 · 15 citations*](https://md.research.elamur.ai/free/en/papers/shi-2024-code-correctness-closing-last-mile/)
21. **[RoT: Enhancing Table Reasoning with Iterative Row-Wise Traversals](https://md.research.elamur.ai/free/en/papers/zhang-2025-rot-enhancing-table-reasoning-iterative/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xuanliang Zhang, Dingzirui Wang, Keyan Xu, et al.*2025 · 10 citations*
22. [**100 Days After DeepSeek-R1: A Survey on Replication Studies and More Directions for Reasoning Language Models arXiv:2505.00551**Chong Zhang, Yue Deng, Xiang Lin, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-100-days-after-deepseek/)
23. **[TableLoRA: Low-rank Adaptation on Table Structure Understanding for Large Language Models](https://md.research.elamur.ai/free/en/papers/he-2025-tablelora-low-rank-adaptation-table/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyi He, Yihao Liu, Mengyu Zhou, et al.*2025 · 8 citations*
24. **[TableEval: A Real-World Benchmark for Complex, Multilingual, and Multi-Structured Table Question Answering](https://md.research.elamur.ai/free/en/papers/zhu-2025-tableeval-real-world-benchmark-complex/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Junnan Zhu, Jingyi Wang, Bohan Yu, et al.*2025 · 7 citations*
25. **[Weaver: Interweaving SQL and LLM for Table Reasoning](https://md.research.elamur.ai/free/en/papers/khoja-2025-weaver-interweaving-sql-llm-table/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Rohit Khoja, Devanshu Gupta, Yanjie Fu, et al.*2025 · 6 citations*
26. **[When TableQA Meets Noise: A Dual Denoising Framework for Complex Questions and Large-scale Tables](https://md.research.elamur.ai/free/en/papers/ye-2026-when-tableqa-meets-noise-dual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shenghao Ye, Yu Guo, Dong Jin, et al.*2026 · 4 citations*
27. **[ClaimDB: A Fact Verification Benchmark over Large Structured Data](https://md.research.elamur.ai/free/en/papers/theologitis-2026-claimdb-fact-verification-benchmark-over/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michael Theologitis, Preetam Prabhu Srikar Dammu, Chirag Shah, et al.*2026 · 2 citations*
28. **[Exploring Generative Process Reward Modeling for Semi-Structured Data: A Case Study of Table Question Answering](https://md.research.elamur.ai/free/en/papers/tang-2026-exploring-generative-process-reward-modeling/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Lei Tang, Wei Zhou, Mohsen Mesgar*2026 · 2 citations*
29. **[Table Question Answering in the Era of Large Language Models: A Comprehensive Survey of Tasks, Methods, and Evaluation](https://md.research.elamur.ai/free/en/papers/zhou-2026-table-question-answering-era-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Zhou, Bolei Ma, Annemarie Friedrich, et al.*2026 · 2 citations*
30. [**AraTable: Benchmarking LLMs' Reasoning and Understanding of Arabic Tabular Data arXiv:2507.18442**Rana Alshaikh, Israa Alghanmi, Shelan Jeawak*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/alshaikh-2025-aratable-benchmarking-llms-reasoning-understanding/)
31. **[CoReTab: Improving Multimodal Table Understanding with Code-driven Reasoning](https://md.research.elamur.ai/free/en/papers/nguyen-2026-coretab-improving-multimodal-table-understanding/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Van-Quang Nguyen, Takayuki Okatani*2026 · 1 citation*
32. **[Efficient Table Retrieval and Understanding with Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-efficient-table-retrieval-understanding-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuoyan Xu, Haoyang Fang, Boran Han, et al.*2026 · 1 citation*
33. **[AdaMix: Adaptive Mixing for Short and Long Reasoning Adapters](https://md.research.elamur.ai/free/en/papers/luo-2026-adamix-adaptive-mixing-short-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Luo, Xiao Yan, Xinyan Li, et al.*2026*
34. **[Asking language models how to represent data for fine-tuning](https://md.research.elamur.ai/free/en/papers/singh-2026-asking-language-models-how-represent/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Usneek Singh, Ananya Singha, Abhijeet Awasthi, et al.*2026*
35. **[Can LLMs Self-Correct Table Reasoning Errors?](https://md.research.elamur.ai/free/en/papers/shaikh-2026-can-llms-self-correct-table/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Farseen Shaikh*2026*
36. **[CodeRise: Bootstrapping LLMs for Ultra Low-Resource Programming Languages via Progressive Self-Refinement Curriculum](https://md.research.elamur.ai/free/en/papers/wen-2026-coderise-bootstrapping-llms-ultra-low/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tengfei Wen, Xuanang Chen, Ben He, et al.*2026*
37. **[Escaping the Sisyphus Dilemma: Experience Replay for Robust Text-to-Optimization Modeling](https://md.research.elamur.ai/free/en/papers/xie-2026-escaping-sisyphus-dilemma-experience-replay/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wantong Xie, Yinghao Chen, Yi-Xiang Hu, et al.*2026*
38. **[MavenCoder: Competitive Code Generation via Model Adaptive Planning Strategies and Multi-Perspective Verification Enhancement](https://md.research.elamur.ai/free/en/papers/xu-2026-mavencoder-competitive-code-generation-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**ZhenChun Xu, Yi Cai, Dajun Zheng, et al.*2026*
39. **[Mixture-of-Minds: Multi-Agent Reinforcement Learning for Table Understanding](https://md.research.elamur.ai/free/en/papers/zhou-2026-mixture-minds-multi-agent-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuhang Zhou, Mingrui Zhang, Ke Li, et al.*2026*
40. **[NG-Router: Graph-Supervised Multi-Agent Collaboration for Nutrition Question Answering](https://md.research.elamur.ai/free/en/papers/shi-2026-ng-router-graph-supervised-multi/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Kaiwen Shi, Zheyuan Zhang, Zhengqing Yuan, et al.*2026*
41. **[PaT: Planning-after-Trial for Efficient Test-Time Code Generation](https://md.research.elamur.ai/free/en/papers/yoon-2026-pat-planning-after-trial-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Youngsik Yoon, Sungjae Lee, Seockbean Song, et al.*2026*
42. **[SMART: Semantic Header Flattening and Pseudo-Code-Style Reasoning for LLM-based Complex Table Question Answering](https://md.research.elamur.ai/free/en/papers/zhang-2026-smart-semantic-header-flattening-pseudo/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yongshuo Zhang, Jixiong Chen, Kaihe xu, et al.*2026*
43. **[Table-R1: Region-based Reinforcement Learning for Table Understanding](https://md.research.elamur.ai/free/en/papers/wu-2026-table-r1-region-based-reinforcement/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenhe Wu, Jian Yang, Zhongjiang He, et al.*2026*
44. **[Towards Robust Real-World Spreadsheet Understanding with Multi-Agent Multi-Format Reasoning](https://md.research.elamur.ai/free/en/papers/ren-2026-robust-real-world-spreadsheet-understanding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Houxing Ren, Mingjie Zhan, Zimu Lu, et al.*2026*
45. **[TRN-R1-Zero: Text-rich Network Reasoning via LLMs with Reinforcement Learning Only](https://md.research.elamur.ai/free/en/papers/liu-2026-trn-r1-zero-text-rich/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yilun Liu, Ruihong Qiu, Zi Huang*2026*
46. **[TrustTable: A Neuro-Symbolic Auditing Framework for Faithful Table QA](https://md.research.elamur.ai/free/en/papers/zhao-2026-trusttable-neuro-symbolic-auditing-framework/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guangzhen Zhao, Dechang Kong, Tongyu Wu, et al.*2026*
47. **[Verify Before You Commit: Towards Faithful Reasoning in LLM Agents via Self-Auditing](https://md.research.elamur.ai/free/en/papers/yuan-2026-verify-before-you-commit-faithful/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenhao Yuan, Chenchen Lin, Jian Chen, et al.*2026*
48. **[Survey on Key Technologies for Large Language Model Pre-training Systems (大语言模型预训练系统关键技术综述)](https://md.research.elamur.ai/free/en/papers/gao-2025-key-technologies-large/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yanjie Gao (高彦杰), Yueguo Chen (陈跃国)*2025*

241 more citing papers of our library have no page here yet.

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